Gambling chip recognition system

ABSTRACT

A computer implemented gambling chip recognition system having the ability to capture an image of a stack of gambling chips and automatically processing the image to determine the number of chips within the stack and the value of each. The system processor determines the classification for each chip in a stack by way of processing performed in real time on the image of the stack of gambling chips. The system further includes the ability to communicate the information derived from the stack of gambling chips to a video monitor and the ability to communicate the information to a main database where information is being compiled and stored about an individual gambler.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of and claims priority tocommonly owned and co-pending U.S. patent application Ser. No.11/072,173, filed on Mar. 4, 2005, entitled “GAMBLING CHIP RECOGNITIONSYSTEM”, which is a continuation application of and claims priority toU.S. patent application Ser. No. 10/385,150, filed on Mar. 10, 2003,entitled “GAMBLING CHIP RECOGNITION SYSTEM”, now abandoned, which is acontinuation of and claims priority to U.S. patent application Ser. No.09/115,328, filed on Jul. 14, 1997, entitled “GAMING DEVICE WITH WRITEONLY MASS STORAGE”, now U.S. Pat. No. 6,532,297, which is acontinuation-in-part of and claims priority to U.S. patent applicationSer. No. 08/962,915, filed on Oct. 27, 1997, entitled “GAMING DEVICEWITH WRITE ONLY MASS STORAGE”, now U.S. Pat. No. 5,781,647, which is acontinuation of and claims priority to U.S. patent application Ser. No.08/539,779, filed on Oct. 5, 1995, entitled “GAMING DEVICE WITH WRITEONLY MASS STORAGE”, now abandoned, all of which are incorporated hereinin their entirety and for all purposes.

APPENDIX

The specification includes an Appendix which includes 133 pages. Theappendix includes computer source code of one preferred embodiment ofthe invention. In other embodiments of the invention, the inventiveconcept may be implemented in other computer code, in computer hardware,in other circuitry, in a combination of these, or otherwise. TheAppendix is hereby incorporated by reference in its entirety and isconsidered to be a part of the disclosure of this specification.

FIELD OF THE INVENTION

The present invention relates to a computer implemented system forcapturing and processing an image of a stack of gambling chips forcounting the number of chips and determining the value of each withinthe stack.

BACKGROUND OF THE INVENTION

In the casino business there is an established reward/perk system thatis used to determine the level of complimentary benefits valuedcustomers should receive. Presently, this system is managed andperformed by a person such as a casino supervisor/floor manager. Thesupervisor/floor manager keeps detailed notes about certain players andtries to determine over an extended period, the length of time a playergambles, the total amount of money bet in one sitting, the averageamount wagered at each bet, etc. By knowing the value of a player'swagers and their gambling habits, the casino decides which players areto receive complimentary benefits. The level of benefits is determinedby a player's level of gambling.

Presently, a player's level of gambling is determined solely by thenotes of the gambling floor supervisor/manager. This is a verysubjective system that is often difficult to maintain because afloor/manager cannot watch all players at all times to get accurateinformation on betting habits.

There is a need for a system that assists gambling operations at casinosin accurately tracking the gambling habits of its customers. Such asystem would be helpful to a casino by making the reward/perk systemmore consistent. The reward/perk system would better serve its purposebecause the guess work would be taken out of determining a player'sgambling habits. Knowing exactly the length of the time played, amountof money bet and average amount wagered at each bet would be veryhelpful in providing the right incentives and complimentary benefits(free meals, limo, room, etc.) to the right players. Such a system couldalso be used to determine a player's pre-established credit rating.

DESCRIPTION OF THE PRIOR ART

In the past, gambling chip recognition systems such as that disclosed inU.S. Pat. No. 4,814,589 to Storch et al. involved counting gamblingchips and detecting counterfeit chips using a binary code placed on theedge of the chip. The system is designed to count chips and detectcounterfeits at a gaming table while the chips are in a rack. Using thisdata, a casino could monitor the number of available chips and otherstatistical information about the activity at individual tables. One ofthe problems with the system disclosed in U.S. Pat. No. 4,814,589 isthat the system requires the disc-like objects, such as gambling chips,coins, tokens, etc., have machine readable information encoded about theperiphery thereof. Another system having similar problems is disclosedin U.S. Pat. No. 5,103,081 to Fisher. It describes a gambling chip witha circular bar code to indicate the chips denomination, authenticity andother information. The chip validating device rotates the chip in orderto read the circular bar code.

The above mentioned prior art systems are particularly cumbersome inthat they require chips to be housed within a particular system androtated to be read or positioned at the right angle or in a rack so thatthe information can be taken from the periphery of the chips. There is aneed for a system that can determine the value of gambling chips withoutencoding the periphery of each chip to enable system determination ofits value. There is a need for a system that can determine the value ofa chip without it being housed within a special reading device. There isa need for a system that can read a conventionally styled,conventionally fabricated chip that is positioned at any angle on agaming table in the betting position. Such a system could cut down oncasino expenses by deleting the cost to encode such chips with readableinformation.

SUMMARY OF THE INVENTION

The present invention is a casino gambling chip recognition system thatprovides for the automatic determination of the number of chips within astack of gambling chips and the value of each chip within the stackthrough the use of a classification scheme stored in the computerwherein the classification scheme may utilize data (parameters) relatedto the geometry, color, feature pattern and size of each type (value) ofchip in a preselected family of chips. The classification scheme data isused as a reference for a real time captured image of the stack ofgambling chips. The system captures an image of the stack of gamblingchips and processes the image by first detecting the boundaries of eachchip in the image and then analyzing the degree of consistency betweenthe data extracted from a given chip's area within the image and theclassification scheme's parameters for all possible chip types. Thesystem assigns the chip the value for which the classification scheme'sparameters are most consistent with the data extracted from that chip'sarea within the image, provided that the degree of consistency isgreater than some predefined minimum acceptable degree of consistency.If none of the classification parameters for any chip type aresufficiently consistent with the extracted data for a given chip in theimage, that chip is assigned an “undefined” value. When the analysis ofthe extracted data from each chip position in the image of the stack hasbeen completed, the system displays the total number of chips which werefound and their total monetary value, obtained by summing all thedefined and assigned chip values from that image. The system alsoprovides the communication of the number and value of chips wagered byplayers to a main computer for storage in a centralized player database. It may also log the occurrences of chips for which an assignedvalue could not be defined.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram representation of a system which can be usedto capture and process a stack of gambling chips in accordance with thepresent invention;

FIG. 2 is a graphical representation of the captured image of a stack ofgambling chips after being digitized by the frame grabber shown in FIG.1; and

FIG. 3 is a diagram indicating the data structures and data flow in thecurrent embodiment.

GENERAL DESCRIPTION OF THE INVENTION

The present invention is a gambling chip recognition system comprising aprocessor, data storage, an imager and a communication link. Thegambling chip recognition system images a stack of gambling chips. Theimage of the gambling chip stack is processed by the processor to firstderive from the image the locations of the chips within the stack andsecondly the type (value) of each chip within the stack. The number ofchips in the stack and the value of each chip within the stack may becommunicated by way of a real time display monitor or to another mainsystem database, via the communication link, where information iscollected about individual gamblers.

DETAILED DESCRIPTION OF THE INVENTION

As required, detailed embodiments of the present invention are disclosedherein. However, it is to be understood that the disclosed embodiment ismerely exemplary of the invention, which may be embodied in variousforms. Therefore, specific structural and functional details disclosedherein are not to be interpreted as limiting but rather as the basis forthe claims and as a representative basis for teaching one skilled in theart to employ the present invention in virtually any appropriatelydetailed system.

Referring to the drawings, an embodiment of the gambling chiprecognition system is illustrated generally in FIG. 1. Gambling chiprecognition system 10 is a microprocessor based system which includes aprocessor 12, data storage 14, an imager 16, a digitizer 18, a monitor20 and a communication link. The data storage 14 will typicallyaccommodate both short-term data storage, for items such as the mostrecent stack images, and longer-term storage, for items such as theparameters characterizing the set of chips being used and theclassification software itself. In the embodiment shown in FIG. 1, astack of gambling chips is imaged by a video camera 16 and digitized bythe frame grabber digitizer 18. During data analysis by the processor 12a digitized image is accessed (typically through normal operating systemmemory and/or file management software) in data storage 14 as an arrayof digital data representative of the gambling chip stack which wasimaged. The processor processes the data in accordance with acomputational program to derive from the image the count of chips andthe value of each chip within the stack. The results may be communicatedto the system user by way of a video monitor 20 or communicated toanother system where the resultant information is added to a playerdatabase within the main computer 22 where information is collectedabout individual gamblers. It is to be understood that this invention isnot limited to the above-mentioned methods for communicating resultantinformation. The above methods are listed as examples of methods used inthe embodiment disclosed in FIG. 1.

The gambling chip recognition system imager 16 is comprised of aplurality of video cameras, one for each gambling position on the gamingtable. Each camera being commercially available and using conventionalrasters and scanning rates. The gambling chip recognition system 10illustrated in FIG. 1, shows only one video camera 16. It is to beunderstood that the present embodiment can utilize any number of videocameras. The number of cameras is determined by the number of gamblingpositions that need to be monitored. For purposes of illustration andsimplifying the description, one camera is described and shown.

The imager 16 may be implemented in a plurality of different ways. Forexample, in another embodiment (not shown), the imager 16 is a highresolution camera mounted in relation to a gaming table such that a fullview of all betting positions are within the camera's field of view. Thecamera continuously images all gambling chip stacks at the gaming tablebetting positions and generates frames of video signals representativethereof. In another embodiment, the imager is a single camera having apan-tilt mechanism employed whereby the camera is repositioned andrefocused on each gambling chip pile separately. It is to be understoodthat other embodiments of the imager may be utilized and that structuralor logical changes to the system may be made without departing from thescope of the present invention.

The digitizer 18 is electrically connected to the imager 16 andprocessor 12. The digitizer 18 is controlled by processor 12 anddigitizes frames of video signals currently being generated by videocamera 16 when commanded by the processor 12. Camera 16 continuouslyimages a stack of gambling chips through its objective lens andgenerates frames of video signals representative thereof. The digitizer18 produces two dimensional arrays of digital pixel valuesrepresentative of the intensity and/or color of the pixel values of thevideo images captured by camera 16 at corresponding discrete pixellocations. An image array having pixel values PVr,c corresponding to astack of gambling chips is illustrated in FIG. 2. Image arrays areformed by horizontal rows and vertical columns of pixel values (PVr,c).

In the embodiment shown in FIG. 1, the digitizer 18 captures a frame ofa video signal generated by video camera 16 and digitizes the videoimage into an array of r=640 rows by c=480 columns of N-bit pixelvalues. The number of bits (N) in a pixel value is dependent upon theclassification scheme employed. The classification scheme employed maybe a grey-scale or color digital scale representation having N bits ofimage data for each pixel. The present embodiment utilizes 24 bits(N=24) of image data to represent an RGB color scale format. Each pixelin the 640 by 480 matrix of pixels consists of red, green and blue colorcomponents. Within each pixel having 24 bits of data, there are 8 bitsof data representing red, 8 bits of data representing green and 8 bitsof data representing blue. It can be appreciated that quantifying thethree color components for each pixel in accordance with the abovedescribed 24 bit format provides up to 2.sup.24 color combinations. Itis to be understood that there are other formats and embodiments forrepresenting color pixel data. In some situations, the pixel data formatmay depend upon the particular CPU (Central Processing Unit), operatingsystem, or other software used in the host computer system.

Image data from the digitizer 18 is stored in data storage 14, whichprovides computational access to derived data as well as to the acquiredimage. The data storage 14 may incorporate digital and/or analog storagedevices, including conventional RAM, conventional disk, or a byte-sizedregister which passes bytes of digital data to the processor in a mannerwhich permits serial access to the data. The serial stream of dataflowing through the register into the processor may flow in a mannerconsistent with the computation even though only one byte may beavailable at each computational cycle.

The communications link 20 constitutes the devices which forward theresults of the count and chip value determination performed by theprocessor. These devices include a video display whereby an operator cansee the results of the processing displayed as a dollar value and countof the stack of chips, as well as digital communications whereby thedata is conveyed to another computing system, i.e., via ethernet,wherein the betting information is stored in a conventional databasecontaining an individual's transaction history.

The processor is a commercially available processor such as an IntelPentium which permits manipulation of the digitized image to enable thederivation of chip information from the digital representation of thestack of gambling chips. The processing may be carried out entirely withone or more digital processors, but analog processing may also be used(for example, in edge detectors or various data conversion operations).The processing may be implemented in hardware, firmware, andor/software. The processing which needs to be performed includes (1)detection of the approximately horizontal edges at the upper and loweredges of each chip, (2) detection of the approximately vertical edges ofthe various “features” (for example, vertical strips of certain colors)occurring along the visible portion of the chip, (3) segmentationprocessing, during which the observed feature sequence for a chip isanalyzed for compatibility with the predefined canonical featuresequences of each of the chip types of the chip set in use, (4)classifying the chip with the value of the chip type whose featuresequence is most consistent with the observed feature sequence, and (5)incorporating the classified values of all the chips in the stack into agrand total value which is reported for the current stack.

FIG. 3 presents a more detailed view of the data flow through thevarious processing steps which are used in this embodiment. Dataprocessing begins with the acquisition of an original image 100,consisting of red, green, and blue component images, each of which is640 columns by 480 rows by 8 bits. This is converted to a Log Image 102by scaling and taking the logarithm of each 8-bit component image, withthe resultant pixels stored as 16-bits per component. The Log Imagepixels are approximately proportional to the logarithm of the originallight level. Thus, subsequent convolution using a kernel which generates“vertical edge” differences from this image will produce edge imagevalues which are primarily related to the relative diffuse reflectioncoefficient on the two sides of an edge, irrespective of the absolutelight intensity at the edge.

Because the fine structure of the vertical edges is not as important assignal-to-noise ratio, the next processing stage generates a ReducedResolution Image 104, with 320 columns by 240 rows having 16 bits percomponent, using the average of one 2.times.2 pixel group in the LogImage 102 to create one pixel in the Reduced Resolution Image 104.

Next, a Vertical Edge Image 106 is calculated by applying a verticaledge extracting kernel to the Reduced Resolution Image 104 (performingthis operation independently on each of the three color components).This kernel consists of seven identical rows (to enhance signal to noiseratio by vertical averaging), each of which consists of the followingseven coefficients: −1, −1, 0, 0, 0, 1, 1.

The Original Image 100 is also used as a source of horizontal edge(layer lines) extraction. This begins with a “despeckling” process,which suppresses specular highlights in the original image by (1)generating a total luminance image from the original r,g,b image, (2)locating anomalous horizontal segments in which a luminance pixel ofsufficient brightness is surrounded by sufficiently dimmer left andright near-neighbors, and (3) replacing original r, g, and b pixels byan interpolation between the corresponding (r, g, or b) pixels at theendpoints of the anomalous segment, yielding the Despeckled Image 108.The Despeckled Image 108 is smoothed by applying a three column wide byseven row high unsharp mask, yielding an Unsharp Smoothed Image 110which will be used for extraction of smooth color values in subsequentprocessing.

The Despeckled Image 100 is also used to generate a Horizontal LineImage 112 by (1) generating, at each pixel location, for each component(r, g, and b), five consecutive rows of data, each of which ishorizontally averaged (using a thirteen column wide averaging interval),(2) calculating absolute differences between the center row average andits upper and lower neighbor rows' averages, (3) calculating an absolutedifference between the center row average and the average of all fourneighboring row averages, and (4) calculating a final, monochromaticpixel value of the Horizontal Line Image 112 based on a weighted sum ofall these differences.

To build up a signal-to-noise ratio before edge detection, groups ofthirty two columns at a time in Horizontal Line Image 112 are averagedinto “Macrocolumns” 114, of which there are twenty, each of which is 480elements long. Each of these is first vertically smoothed by averagingthree consecutive elements, then scanned, top-to-bottom, for edges. Whena change of at least ten is found over a span of two columns, the firstsubsequent local maximum is declared to be an edge and its location isstored in that macrocolumn's Edge List 116.

The twenty raw Edge Lists 116 are further processed by a “corroborationalgorithm” which rejects edges which are not sufficiently closevertically to edges in adjacent macrocolumns and groups the admissibleedges into global (over all macrocolumns) Corroborated Edge Lists 118such that top edges of the top chip have an index of zero in allmacrocolumns where they are found, top edges of the second chip alwayshave an index of one, etc.

The row coordinates to use in subsequent horizontal scanning of a givenchip are obtained by (1) interpolating and extrapolating the definededge (row coordinate) values into all macrocolumns where they are notalready defined and (2) adding an offset equivalent to approximately onehalf of the (known in advance) chip thickness to the top edge coordinatefor a given chip at a given macrocolumn. The resultant array of twentyrow numbers (one for each macrocolumn) for a given chip is the RowNumber of Chip Center 120.

The Row Number of Chip Center 120 is used to select r, g, and b valuesfrom Unsharp Smoothed Image 110, yielding one-dimensional arrays ofSmoothed RGB's Along Chip Center 122. The Row Number of Chip Center 120is also used to select r, g, and b values from V Edge Image 106,yielding one-dimensional arrays of V Edge RGB's Along Chip Center 122.The Smoothed RGB's Along Chip Center 120 are also converted, by normalRGB to HLS conversion equations, into suitably scaled, Smoothed HLS'sAlong Chip Center 124.

Segmentation of data extracted along the chip center is performed bydeclaring a feature edge to exist at any column where either (1) the VEdge r, g, or b value exceeds a certain threshold, or (2) a more gradualhue change of sufficient magnitude occurs (provided that the luminanceand saturation values at that location are sufficiently high for huevalues to be stable), or (3) a more gradual saturation change ofsufficient magnitude occurs (provided that the luminance and saturationvalues at that location are sufficiently high for saturation values tobe stable. The initial and final column numbers of each such edge arestored, along with the total number of such edges, in Edge CoordinatesAlong Chip Center 126.

Next, the observed sequence of extracted features for a given chip iscompared with Predefined Segment Templates 128, which define the hue.luminance, saturation, and length limits allowed for each feature ofeach denomination in the current chip set. (In actuality, hue isrepresented by two values, called Hx and Hy, representing the x and yprojections of the angular coordinate, Hue.) For each candidatedenomination (possible chip value), a Score Structure 130 is computed,including the number of each feature type which was encountered and themaximum encountered total length of contiguous features consistent withthe sequential feature definitions contained in the Template 128 forthat denomination.

Finally, a final Denomination Value 130 is calculated using certainclassification rules. For example, the candidate denomination whichyielded the greatest total length of contiguous features can be chosen,provided that there was at least one occurrence of the longest (or“background” defined feature type for that denomination.

1. A method of determining a value of a stack of a plurality of wageringchips, comprising: capturing image data of a stack of wagering chips,said image data coming from a captured image providing a view wherein aside of said stack of wagering chips is at least as prominent as the topof said stack of wagering chips; determining from the captured imagedata a count of wagering chips; determining from the captured image dataa value of each wagering chip; and determining a value of the stack ofwagering chips using wagering chip value and wagering chip count.
 2. Themethod of claim 1, wherein the count of wagering chips in the stack isdetermined by identifying the boundaries of each wagering chip in thestack.
 3. The method of claim 1, wherein capturing of image data ofmultiple stacks of wagering chips is performed by multiple cameras. 4.The method of claim 1, wherein the value of each wagering chip isdetermined using a classification scheme.
 5. The method of claim 4,wherein the classification scheme uses data related to at least onecharacteristic selected from the group consisting of: geometry, featurepattern and size of each wagering chip.
 6. The method of claim 1,wherein capturing image data is a continuous process.
 7. The method ofclaim 1, wherein the step of determining a count of each wagering chipcomprises digitizing an output from an imager.
 8. The method of claim 1and further comprising displaying at least one determined value, thedetermined values consisting of at least one of wagering chip count,wagering chip value and stack value.
 9. The method of claim 1, whereinthe value of each wagering chip is determined by a color classificationscheme.
 10. The method of claim 9, wherein red, green and blue colorvalues are determined for each wagering chip in the stack.
 11. Themethod of claim 1, wherein the count of chips is determined usinghorizontal edge detection extraction.
 12. The method of claim 1, whereinchip value is determined using vertical edge extraction.
 13. A methodfor determining the number of gambling chips and the value assigned eachgambling chip within a stacked pile of a plurality of gambling chipscomprising: providing image data of the stacked pile of gambling chipssaid image data coming from a captured image providing a view wherein aside of said stack of wagering chips is at least as prominent as the topof said stack of wagering chips; determining from the image data thelocation of individual gambling chips in the stacked pile of gamblingchips; determining from the image data the value of individual gamblingchips in the stacked pile of gambling chips; using the location ofindividual gambling chips to provide a count of gambling chips withinthe stacked pile of gambling chips; using a feature indicating value onindividual gambling chips selected from the group consisting ofgeometry, pattern and size to provide image data relating to the valueof individual gambling chips in the stacked pile of gambling chips; andfrom the count of gambling chips and value of individual gambling chipsin the stacked pile of gambling chips, automatically determining thevalue of the stacked pile of chips.
 14. The method of claim 13 whereinthe image data used to provide a count of individual gambling chips isdigitized data.
 15. The method of claim 13 wherein a total luminanceimage provided from the image data is used to determine the count ofgambling chips in the stacked pile of gambling chips.
 16. The method ofclaim 13 wherein image data of the stacked pile of chips is provided ascontinuous image data.
 17. The method of claim 13 wherein the image datacomprises edges of features on a visible portion of the gambling chipwithin the stacked pile of gambling chips to determine a chip featuresequence for each chip.
 18. The method of claim 13 wherein there aremultiple sources that comprise imagers for providing image data at asingle gaming table, the single gaming table has multiple areas forplacing stacked piles of chips and at least one of the imagers has afield of view that encompasses each one of the multiple areas forplacing stacked piles of chips, and the imagers have a pan tiltmechanism.
 19. The method of claim 13 wherein there are multiple sourcesfor providing image data at a single gaming table.
 20. The method ofclaim 19 wherein the multiple sources for providing image data compriseimagers.
 21. The method of claim 20 wherein the single gaming table hasmultiple areas for placing stacked piles of chips and at least one ofthe imagers has a field of view that encompasses each one of themultiple areas for placing stacked piles of chips.
 22. The method ofclaim 19 wherein said imagers have a pan tilt mechanism.
 23. A method ofdetermining a value of a stack of wagering chips, comprising: capturingan image of a stack of wagering chips, said captured image providing aview wherein a side of said stack of wagering chips is at least asprominent as the top of said stack of wagering chips; determining fromsaid captured image a count of wagering chips; determining from saidcaptured image a value of each wagering chip; and determining a value ofthe stack of wagering chips using wagering chip value and wagering chipcount.
 24. The method of claim 23, wherein the value of each wageringchip is determined using a classification scheme related to at least onewagering chip characteristic selected from the group consisting of:geometry, feature pattern and size of each wagering chip.
 25. The methodof claim 23, wherein said step of determining a value of each wageringchip includes processing information from at least said side of saidstack of wagering chips.
 26. A method of determining a value of a stackof wagering chips, comprising: capturing image data of a stack ofwagering chips using an imager positioned at an angle having asubstantial horizontal component with respect to said stack of wageringchips; determining from said captured image data a count of wageringchips; determining from said captured image data a value of eachwagering chip; and determining a value of said stack of wagering chipsusing wagering chip value and wagering chip count.
 27. The method ofclaim 26, wherein the value of each wagering chip is determined using aclassification scheme related to at least one wagering chipcharacteristic selected from the group consisting of: geometry, featurepattern and size of each wagering chip.
 28. The method of claim 26,wherein said step of determining a value of each wagering chip includesprocessing information from at least a side of said stack of wageringchips.
 29. The method of claim 26, wherein said imager is positionedsuch that a captured image of said stack of wagering chips provides aview wherein a side of said stack of wagering chips is at least asprominent as the top of said stack of wagering chips.
 30. A method ofdetermining a value of a stack of wagering chips, comprising: capturingimage data of a stack of wagering chips; determining from the capturedimage data a count of wagering chips based on the sides of each chip insaid stack of wagering chips; determining from the captured image data avalue of each wagering chip based on the sides of each chip in saidstack of wagering chips; and determining a value of the stack ofwagering chips using wagering chip value and wagering chip count.